Systems | Development | Analytics | API | Testing

APIs are the foundation of modern software ecosystems—connecting applications, services, and databases so information can flow securely and efficiently. But as systems become more complex and businesses demand faster innovation, traditional, manual approaches to API management no longer scale. That’s where AI-powered API gateways come in.

If you’ve ever tracked bugs across half a dozen tools, juggled spreadsheets, or tried to make sense of test results buried in an email thread, you’ve felt the pain of outdated test management. As software development speeds up with agile and CI/CD, the role of test management has changed. What used to be a support function is now central to delivering quality software fast. And if your test management approach hasn’t evolved, it’s holding you back.

Software teams know the drill: deliver faster without sacrificing quality. You’ve heard it before because you live it every day. Testing is often where that pressure hits a breaking point, but it doesn’t have to. At SmartBear, we help developers and testers like you seamlessly integrate automated testing into existing workflows and CI/CD pipelines. That’s why we’ve partnered with AWS CodePipeline to bring powerful, AI-driven test automation to your delivery process.

In today’s digital world, it is essential to be able to deliver high-quality software quickly. Test automation using special tools will automate repetitive test cases, which will give accuracy and speed up delivery. Test automation enables Dev Operationists by assuring continuous testing, which enables earlier bug finding and wider test coverage.

Today, we’re announcing that Kong has acquired OpenMeter, the open source and SaaS leader for real-time usage metering and billing. OpenMeter’s capabilities will be integrated into Kong Konnect, enabling usage-based pricing, entitlements, and invoicing for APIs, events, and AI workloads. This is a huge milestone for Kong, and we’re excited about what this means for our customers and the future of how you build and scale revenue-generating digital products for the agentic AI era.

Most of the times teams spend their time testing that features work correctly under normal conditions. But do you know what happens when the database goes down,the network goes slow or a third party service stops responding? In this case, resilience testing solves this problem by intentionally breaking parts of your system to see how it responds to it. Instead of only testing perfect scenarios, you find real-world failures like server crashes, network issues and service timeouts.

Agentic AI is transforming how businesses operate by enabling systems to handle complex tasks autonomously. Instead of relying on constant human input, these AI systems break down high-level goals into smaller tasks, make decisions independently, and improve continuously through feedback. Here's what you need to know: Key Features: Autonomously manage workflows and processes. Handle multi-step decision-making and problem-solving. Learn and adapt based on performance data.

In today’s rapid web development, faultless user experience is a requirement. Old school test tools tend to come up short with slow speeds, flakiness, and complicated setups. Cypress testing is a new-generation testing framework designed for the web with fast, predictable, and delightful testing for end-to-end, UI, and component-level tests – all in a browser-native context.

Ever feel like you're fighting an uphill battle with your API strategy? You're building APIs faster than ever, but somehow everything feels harder. Wasn’t API-first supposed to make all this easier? Well, you're not alone. And now industry analysts are noting it as well. New Gartner research on successful API-first integration just came out, and it validates something we've been saying for a while: many organizations are fundamentally misunderstanding what API-first actually means. The result?

The rise of Model Context Protocol (MCP) has given AI agents and large language models (LLMs) a standardized way to talk to external tools, APIs, and data sources. In theory, it solves the messy integrations and custom connectors that have slowed down real-world agent adoption. A clean protocol should mean smooth interoperability. However, we’re observing certain patterns of fragmentation. Each MCP server runs in isolation. Agents have to handle multiple connections.